Input-to-state stabilizing sub-optimal NMPC with an application to DC-DC converters

M. Lazar, W.P.M.H. Heemels, B.J.P. Roset, H. Nijmeijer, P.P.J. Bosch, van den

Research output: Contribution to journalArticleAcademicpeer-review

40 Citations (Scopus)
1 Downloads (Pure)


This article focuses on the synthesis of computationally friendly sub-optimal nonlinear model predictive control (NMPC) algorithms with guaranteed robust stability. To analyse the robustness of the MPC closed-loop system, we employ the input-to-state stability (ISS) framework. To design ISS sub-optimal NMPC schemes, a new Lyapunov-based method is proposed. ISS is ensured via a set of constraints, which can be specified as a finite number of linear inequalities for input affine nonlinear systems. Furthermore, the method allows for online optimization over the ISS gain of the resulting closed-loop system. The potential of the developed theory for the control of fast nonlinear systems, with sampling periods below 1 ms, is illustrated by applying it to control a Buck-Boost DC-DC converter.
Original languageEnglish
Pages (from-to)890-904
Number of pages15
JournalInternational Journal of Robust and Nonlinear Control
Issue number8
Publication statusPublished - 2008


Dive into the research topics of 'Input-to-state stabilizing sub-optimal NMPC with an application to DC-DC converters'. Together they form a unique fingerprint.

Cite this